Multiscale and morphological analysis of microvascular patterns depicted in contrast-enhanced ultrasound images

Super-Resolution Ultrasound Imaging for Monitoring the Therapeutic Efficacy of a Vascular Disrupting Agent in an Animal Model of Breast Cancer

OBJECTIVE

Evaluate the use of super-resolution ultrasound (SRUS) imaging for the early detection of tumor response to treatment using a vascular-disrupting agent (VDA).

METHODS

A population of 28 female nude athymic mice (Charles River Laboratories) were implanted with human breast cancer cells (MDA-MB-231, ATCC) in the mammary fat pad and allowed to grow. Ultrasound imaging was performed using a Vevo 3100 scanner (FUJIFILM VisualSonics Inc) equipped with the MX250 linear array transducer immediately before and after receiving bolus injections of a microbubble (MB) contrast agent (Definity, Lantheus Medical Imaging) via the tail vein. Following baseline ultrasound imaging, VDA drug (combretastatin A4 phosphate, CA4P, Sigma Aldrich) or control saline was injected via the placed catheter. After 4 or 24 hours, repeat ultrasound imaging along the same tumor cross-section occurred. Direct intratumoral pressure measurements were obtained using a calibrated sensor. All raw ultrasound data were saved for offline processing and SRUS image reconstruction using custom MATLAB software (MathWorks Inc). From a region encompassing the tumor space and the entire postprocessed ultrasound image sequence, time MB count (TMC) curves were generated in addition to traditional SRUS maps reflecting MB enumeration at each pixel location. Peak enhancement (PE) and wash-in rate (WIR) were extracted from these TMC curves. At termination, intratumoral microvessel density (MVD) was quantified using tomato lectin labeling of patent blood vessels.

RESULTS

SRUS images exhibited a clear difference between control and treated tumors. While there was no difference in any group parameters at baseline (0 hour, P > .09), both SRUS-derived PE and WIR measurements in tumors treated with VDA exhibited significant decreases by 4 (P = .03 and P = .05, respectively) and 24 hours (P = .02 and P = .01, respectively), but not in control group tumors (P > .22). Similarly, SRUS derived microvascular maps were not different at baseline (P = .81), but measures of vessel density were lower in treated tumors at both 4 and 24 hours (P < .04). An inverse relationship between intratumoral pressure and both PE and WIR parameters were found in control tumors (R2 > .09, P < .03).

CONCLUSION

SRUS imaging is a new modality for assessing tumor response to treatment using a VDA.

Endothelial ERα promotes glucose tolerance by enhancing endothelial insulin transport to skeletal muscle

The estrogen receptor (ER) designated ERα has actions in many cell and tissue types that impact glucose homeostasis. It is unknown if these include mechanisms in endothelial cells, which have the potential to influence relative obesity, and processes in adipose tissue and skeletal muscle that impact glucose control. Here we show that independent of impact on events in adipose tissue, endothelial ERα promotes glucose tolerance by enhancing endothelial insulin transport to skeletal muscle. Endothelial ERα-deficient male mice are glucose intolerant and insulin resistant, and in females the antidiabetogenic actions of estradiol (E2) are absent. The glucose dysregulation is due to impaired skeletal muscle glucose disposal that results from attenuated muscle insulin delivery. Endothelial ERα activation stimulates insulin transcytosis by skeletal muscle microvascular endothelial cells. Mechanistically this involves nuclear ERα-dependent upregulation of vesicular trafficking regulator sorting nexin 5 (SNX5) expression, and PI3 kinase activation that drives plasma membrane recruitment of SNX5. Thus, coupled nuclear and non-nuclear actions of ERα promote endothelial insulin transport to skeletal muscle to foster normal glucose homeostasis.

Assessment of Transarterial Chemoembolization Using Super-resolution Ultrasound Imaging and a Rat Model of Hepatocellular Carcinoma

OBJECTIVE

Hepatocellular carcinoma (HCC) is a highly prevalent form of liver cancer diagnosed annually in 600,000 people worldwide. A common treatment is transarterial chemoembolization (TACE), which interrupts the blood supply of oxygen and nutrients to the tumor mass. The need for repeat TACE treatments may be assessed in the weeks after therapy with contrast-enhanced ultrasound (CEUS) imaging. Although the spatial resolution of traditional CEUS has been restricted by the diffraction limit of ultrasound (US), this physical barrier has been overcome by a recent innovation known as super-resolution US (SRUS) imaging. In short, SRUS enhances the visible details of smaller microvascular structures on the 10 to 100 µm scale, which unlocks a host of new clinical opportunities for US.

METHODS

In this study, a rat model of orthotopic HCC is introduced and TACE treatment response (to a doxorubicin-lipiodol emulsion) is assessed using longitudinal SRUS and magnetic resonance imaging (MRI) performed at 0, 7 and 14 d. Animals were euthanized at 14 d for histological analysis of excised tumor tissue and determination of TACE response, that is, control, partial response or complete response. CEUS imaging was performed using a pre-clinical US system (Vevo 3100, FUJIFILM VisualSonics Inc.) equipped with an MX201 linear array transducer. After administration of a microbubble contrast agent (Definity, Lantheus Medical Imaging), a series of CEUS images were collected at each tissue cross-section as the transducer was mechanically stepped at 100 μm increments. SRUS images were formed at each spatial position, and a microvascular density metric was calculated. Microscale computed tomography (microCT, OI/CT, MILabs) was used to confirm TACE procedure success, and tumor size was monitored using a small animal MRI system (BioSpec 3T, Bruker Corp.).

RESULTS

Although there were no differences at baseline (p > 0.15), both microvascular density levels and tumor size measures from the complete responder cases at 14 d were considerably lower and smaller, respectively, than those in the partial responder or control group animals. Histological analysis revealed tumor-to-necrosis levels of 8.4%, 51.1% and 100%, for the control, partial responder and complete responder groups, respectively (p < 0.005).

CONCLUSION

SRUS imaging is a promising modality for assessing early changes in microvascular networks in response to tissue perfusion-altering interventions such as TACE treatment of HCC.

Evaluation of Nonlinear Contrast Pulse Sequencing for Use in Super-Resolution Ultrasound Imaging

The use of super-resolution ultrasound (SR-US) imaging greatly improves visualization of microvascular structures, but clinical adoption is limited by long imaging times. This method depends on detecting and localizing isolated microbubbles (MBs), forcing the use of a dilute contrast agent concentration. Contrast-enhanced ultrasound (CEUS) image acquisition times as long as minutes arise as the localization of thousands of MBs are acquired to form a complete SR-US image. In this article, we explore the use of nonlinear CEUS strategies using nonlinear fundamental contrast pulse sequencing (CPS) to increase the contrast-to-tissue ratio (CTR) and compare MB detection effectiveness to linear B-mode CEUS imaging. The CPS compositions of amplitude modulation (AM), pulse inversion (PI), and a combination of the two (AMPI) were studied. A simulation study combined the Rayleigh-Plesset-Marmottant (RPM) model of MB characteristics and a nonlinear tissue model using the k-Wave toolbox for MATLAB (MathWorks Inc., Natick, MA, USA). Validation was conducted using an in vitro flow phantom and in vivo in the rat hind-limb. Imaging was performed with a programmable US scanner (Vantage 256, Verasonics Inc., Kirkland, WA, USA) and customized to transmit a set of basis US pulses from which both B-mode US (frame rate (FR) of 800 Hz) and multiple nonlinear CPS compositions (FR of 200 Hz) could be assessed from identical in vitro and in vivo datasets using a near simultaneous method. The simulations suggest that MB characteristics, such as diameter and motion, help to predict which US imaging strategy will enhance MB detection. The in vitro and in vivo US imaging studies revealed that different subpopulations of polydisperse MB contrast agents were detected by linear imaging and by each different nonlinear CPS composition. The most effective single imaging strategy at a 200-Hz FR was found to be B-mode US imaging. However, a combination of B-mode US imaging with a nonlinear CPS imaging strategy was more effective in detecting MBs in vivo at all depths and was shown to shorten image acquisition time by an average of 33.3%-76.7% when combining one or more CPS sequences.

Multiscale computational modeling of cancer growth using features derived from microCT images

Advances in medical imaging technologies now allow noninvasive image acquisition from individual patients at high spatiotemporal resolutions. A relatively new effort of predictive oncology is to develop a paradigm for forecasting the future status of an individual tumor given initial conditions and an appropriate mathematical model. The objective of this study was to introduce a comprehensive multiscale computational method to predict cancer and microvascular network growth patterns. A rectangular lattice-based model was designed so different evolutionary scenarios could be simulated and for predicting the impact of diffusible factors on tumor morphology and size. Further, the model allows prediction-based simulation of cell and microvascular behavior. Like a single cell, each agent is fully realized within the model and interactions are governed in part by machine learning methods. This multiscale computational model was developed and incorporated input information from in vivo microscale computed tomography (microCT) images acquired from breast cancer-bearing mice. It was found that as the difference between expansion of the cancer cell population and microvascular network increases, cells undergo proliferation and migration with a greater probability compared to other phenotypes. Overall, multiscale computational model agreed with both theoretical expectations and experimental findings (microCT images) not used during model training.

Three-dimensional visualization and improved quantification with super-resolution ultrasound imaging - validation framework for analysis of microvascular morphology using a chicken embryo model

The purpose of this study was to improve the morphological analysis of microvascular networks depicted in three-dimensional (3D) super-resolution ultrasound (SR-US) images. This was supported by qualitative and quantitative validation by comparison to matched brightfield microscopy and traditional B-mode ultrasound (US) images. Contrast-enhanced US (CEUS) images were collected using a preclinical US scanner (Vevo 3100, FUJIFILM VisualSonics Inc.) equipped with an MX250 linear array transducer. CEUS imaging was performed after administration of a microbubble (MB) contrast agent into the vitelline network of a developing chicken embryo. Volume data was collected by mechanically scanning the US transducer throughout a tissue volume-of-interest in 90μm step increments. CEUS images were collected at each increment and stored as in-phase/quadrature data (2000 frames at 152 frames per sec). SR-US images were created for each cross-sectional plane using established data processing methods. All SR-US images were then used to reconstruct a final 3D volume for vessel diameter (VD) quantification and for surface rendering. VD quantification from the 3D SR-US data exhibited an average error of 6.1% ± 6.0% when compared with matched brightfield microscopy images, whereas measurements from B-mode US images had an average error of 77.1% ± 68.9%. Volume and surface renderings in 3D space enabled qualitative validation and improved visualization of small vessels below the axial resolution of the US system. Overall, 3D SR-US image reconstructions depicted the microvascular network of the developing chicken embryos. Improved visualization of isolated vessels and quantification of microvascular morphology from SR-US images achieved a considerably greater accuracy compared to B-mode US measurements.

Three-dimensional evaluation of microvascular networks using contrast-enhanced ultrasound and microbubble tracking

Evaluating tumor microvascular networks with use of contrast-enhanced ultrasound (CEUS) imaging and one-dimensional (1D) linear array transducers have inherit limitations as tumors exist in volume space. The use of a mechanical sweep allows users to overcome this limitation. To that end, we have developed a new method by which a 1D linear array transducer can be mechanically scanned over a region-of-interest to capture a volume of data allowing for the evaluation of microvasculature structures in 3D space. After intravascular injection of a microbubble (MB) contrast agent into a developing chicken embryo, a sequence of CEUS images were acquired using a Vevo 3100 scanner (VisualSonics Inc) and taken at multiple tissue cross-sections. The CEUS images were processed with a singular value filter (SVF) to help remove any clutter signal. MB localization was performed, and frame-to-frame MB movement was analyzed to produce spatial maps depicting blood flow and velocity at each tissue cross-section. Reconstruction of all images allowed visualization of microvascular networks and blood velocity distribution in volume space.